logseq/pages/hls__SATToSE_2023_paper_3_1683215144921_0.md

file:: SATToSE_2023_paper_3_1683215144921_0.pdf file-path:: ../assets/SATToSE_2023_paper_3_1683215144921_0.pdf

• available tools for vulnerability detection, practitioners are puzzled when selecting the most suitable approach to adopt in the projects they work on ls-type:: annotation hl-page:: 1 hl-color:: purple id:: 6453d72a-355e-49c8-a1cd-dfc78228398a
• annot be easily compared ls-type:: annotation hl-page:: 1 hl-color:: purple id:: 6453d72e-9f2d-44e7-8246-a4f5d08aa777
• lack of a detailed comparison among existing approaches for vulnerability detection ls-type:: annotation hl-page:: 1 hl-color:: purple id:: 6453d739-ce48-4f60-bdea-53323e07110a
• new way to compare the tools with each other ls-type:: annotation hl-page:: 1 hl-color:: purple id:: 6453d73f-dc40-4b11-9ef2-e07c5b4f4e0c
• . By performing a multivocal literature review, we plan to gather information about the existing tools for vulnerability detection and the related benchmark ls-type:: annotation hl-page:: 1 hl-color:: purple id:: 6453d74d-01b5-4c36-820d-7e07a48d2199
• How do vulnerability detection tools perform under different benchmarks in terms of detection rates, analysis rates, and output understandability ls-type:: annotation hl-page:: 4 hl-color:: purple id:: 6453d766-87af-460e-81eb-212f7ec13497
• the winners of each of the three categories—i.e., static analyzers, dynamic analyzers, and machine-learning models—will be compared in a “final” bout that will decree the winner on that benchmark ls-type:: annotation hl-page:: 5 hl-color:: purple id:: 6453d7aa-f4f2-4827-8e44-8301495c66c8
• performance metrics ls-type:: annotation hl-page:: 5 hl-color:: purple id:: 6453d81c-957e-49ed-a68e-25096b827aaf
• wide range of metrics commonly adopted in literature for evaluating these kinds of tools, measuring aspects like (i) the discovery rate of vulnerabilities, (ii) the rate of analyzed components (e.g., code elements) per time unit, and (iii) the understandability of the output ls-type:: annotation hl-page:: 5 hl-color:: purple id:: 6453d829-e088-42aa-8de3-9a8981634de2